A Survey on Temporal Reasoning in Artificial Intelligence

Anselma

2004

Int. J. Intell. Syst.

Abstract.Reasoning with temporal constraints is a ubiquitous issue in many computer science tasks, for which many dedicated approaches have been and are being built. In particular, in many areas, including planning, workflow, guidelines and protocol management, one needs to represent and reason with temporal constraints between classes of events (e.g., between the types of actions needed to achieve a goal) and temporal constraints between instances of events (e.g., between the specific actions being executed). The temporal constraints between the classes of events must be inherited by the instances, and the consistency of both types of constraints must be checked. In this paper, we design a general-purpose domain-independent knowledge server dealing with these issues. In particular, we propose a formalism to represent temporal constraints, and we point out two orthogonal parameters that affect the definition of reasoning algorithms operating on them. We then show four algorithms to deal with inheritance and to perform temporal consistency checking (depending on the parameters) and we study their properties. Finally, we report the results we obtained by applying our system to the treatment of temporal constraints in clinical guidelines.

“…10 and 11 and the survey in Ref. 2). Unfortunately, the gap between what can be done in STP and what we want to obtain is quite broad.…”

Section: A Two-layer Approachmentioning

confidence: 85%

Section: Other Constructs Of Itlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A knowledge server for reasoning about temporal constraints between classes and instances of events

Anselma

2004

Int. J. Intell. Syst.

“…Many languages and temporal managers been developed within the AI literature to cope with these Ž forms of constraints see, e.g., the surveys in Vilain et al 1990;Allen 1991a;Allen and . Ž Yampratoom 1993;Vila 1994 . In particular, we recently developed LaTeR Brusoni, .…”

Section: Instances Not Exactly Located In Time Sketchmentioning

confidence: 99%

Integrated Temporal Reasoning with Periodic Events

Computational Intelligence

2000

In many areas of Computer Science, including planning, workflows, guidelines, and protocol management, one has to deal with abstract plans, procedures, or schedules involving temporal constraints between classes of actions that have to be repeated at periodic times and may be instantiated in Ž . different ways for different executions of the plans procedures, schedules . In this paper we propose an integrated framework to deal with both qualitative temporal constraints on classes of actions and temporal constraints between instances of actions, in which temporal reasoning is used to amalgamate both types of constraints and to check their consistency. In particular, we consider an expressive Ž formalism to deal with temporal constraints between classes of actions with special attention to . periodic actions which takes into account different components such as frame times, numeric quantifi-Ž . cation, periods, and qualitative relations. We define the notions of contextual concretization of qualitative temporal constraints between classes and use this notion to formally define the consistency of a knowledge base of temporal constraints between classes and a set of temporal constraints on instances, and to define the algorithm for checking such a consistency. An application for scheduling lessons in a school is shown in an example.

“…51 and 24, and the surveys in Refs. 73,4,71, and 55 and the collection). 28 A relevant part of the specialized approaches to temporal reasoning focused on the treatment of qualitative temporal constraints.…”

Section: Introductionmentioning

confidence: 99%

Toward a comprehensive treatment of temporal constraints about periodic events

2003

Int. J. Intell. Syst.

In this article, we propose an Allen-like approach to deal with different types of temporal constraints about periodic events. We consider the different components of such constraints (thus, unlike Allen, we also take into account quantitative constraints) including frame times, user-defined periods, qualitative temporal constraints, and numeric quantifiers and the interactions between such components. We propose a specialized high-level formalism to represent temporal constraints about periodic events; temporal reasoning on the formalism is performed by a path-consistency algorithm repeatedly applying our operations of inversion, intersection, and composition and by a specialized reasoner about periods and numeric quantification. The high-level formalism has been designed in such a way that different types of temporal constraints about periodic events can be represented in a compact and (hopefully) user-friendly way and path-consistency-based temporal reasoning on the formalism can be performed in polynomial time. We also prove that our definitions of inversion, intersection, and composition and, thus, of our path-consistency algorithm, are correct. This article also sketches the general architecture of the temporal manager for periodic events (TeMP ϩ ), that has been designed on the basis of our approach. As a working example, we show an application of our approach to scheduling in a school.